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antoinecellerier
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code-health

Audit codebases for quality, technical debt, and regression test coverage.

2|Updated Feb 4, 2026
Search Tags:#code quality#code review#best practices#refactoring#technical debt#auditing
One-click install
npx skills add https://github.com/antoinecellerier/les-aiguilles-blanches --skill code-health-antoinecellerier
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: code-health
Source: https://github.com/antoinecellerier/les-aiguilles-blanches/tree/main/.github/skills/code-health
Command: npx skills add https://github.com/antoinecellerier/les-aiguilles-blanches --skill code-health-antoinecellerier

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill provides a structured process for auditing code quality, identifying technical debt, and ensuring engineering best practices are followed.

Core Features & Use Cases

  • Comprehensive Audits: Covers duplication, inconsistency, lifecycle management, error handling, architecture, magic values, and test coverage.
  • Prioritized Findings: Classifies issues by severity (High, Medium, Low, Deferred) for efficient remediation.
  • Use Case: Use this Skill to perform a thorough review of a new feature's codebase before merging, ensuring maintainability and robustness.

Quick Start

Use the code-health skill to audit the codebase for duplication and error handling issues.

Frequently Asked Questions about code-health

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I perform a code health audit to identify technical debt?▼

A code health audit identifies and categorizes technical debt by reviewing duplication, inconsistency, error handling, architecture, magic values, and test coverage. This process provides prioritized findings classified by severity for efficient remediation.

What is the best way to audit code quality before merging a new feature?▼

The best way to audit code quality is a structured review covering lifecycle management, error handling, and regression test coverage. This classifies issues by severity to ensure maintainability and robustness before merging.

How do I categorize technical debt findings by severity for remediation?▼

Categorize technical debt findings by classifying issues into High, Medium, Low, and Deferred severity levels. This prioritized classification enables efficient remediation by focusing on the most critical code health issues first.

Can I use a structured code review process to detect magic values and duplication?▼

Yes, a structured code review process can detect magic values and duplication. The audit comprehensively covers these specific code quality issues alongside inconsistency and error handling to reduce overall technical debt.

Does code health auditing support cross-model consultation for complex architecture issues?▼

Yes, code health auditing supports cross-model consultation for complex architecture issues. It guides a phased exploration process to thoroughly review architecture, lifecycle management, and error handling with verification.

What code quality issues should I look for when auditing technical debt?▼

When auditing technical debt, look for code quality issues including duplication, inconsistency, lifecycle management gaps, error handling flaws, architecture problems, magic values, and missing regression test coverage.

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